In order to encode a picture signal at high efficiency, there has been frequently used a moving picture encoding and decoding system and its device that appropriately encode a picture signal mainly by block. As a typical one, TV Conference system based on International Telegraph and Telephone Standard (ITU-T H. 261 standard) is generally used. By such encoding systems, however, a block-shaped step, i.e., block noise, due to quantizing error is perceived in a decoded picture. Further, it is known that if there is a rapid pixel change such as a character on a flat background, pseudo edge called as mosquito noise occurs in its surrounding. The block-shaped noise can be observed when a step of unnatural, abnormal or artifact brightness, color and the like occurs on a block boundary. In prior art techniques, a smoothing filter for decreasing such a step is utilized against the entire decoded picture or a pixel that exists on the block boundary, to reduce the block-shaped noise.
FIG. 24 is a block diagram of an inter-frame encoding and decoding system of the ITU-T H. 261 standard, and indicates the position at which block-shaped noise reducing process is performed. In this figure, a subtracter 11 generates a difference between an input picture signal 10 and a picture signal 24 of the previous frame that has been encoded, decoded and reconstituted. The difference is encoded in an encoder 12 by means of DCT, quantization and Huffman coding. An encoded error signal 13 is transmitted to a decoder 25, and is again returned to a difference signal in a local decorder 14 by means of inverse Huffman coding, inverse quantization and inverse DCT. This difference signal 15 contains operation errors in the encoder 12 and the local decorder 14, resulting in a value different from the difference generated in the subtracter 11.
Then, the difference signal 15 and the picture signal 24 of the previous frame are added in an adder 16 to generate a picture signal 17, which is then stored in a frame memory 18, standing by for the next picture signal input. In these operations, the processing is performed by block of a picture divided into 8.times.8 dot size.
When taking, in the subtracter 11, the difference between the input picture signal 10 and the previous picture signal 24 from the frame memory 18, there is generally employed technique called motion estimation and compensation. This technique is performed by a motion vector detector 19. Specifically, to obtain a difference between a signal stored in the frame memory 18 and an input signal, the detector 19 reads out the previous picture signal 21 from the frame memory 18, and slide the signal 21 up and down, and right and left, to obtain differences, thereafter, select a slide quantity with which the difference becomes the smallest, as a motion vector 22, which is then transmitted to a decoding side by multiplexing with an error signal 13 that has been multiplexed by a multiplexer 29a. The motion vector 22 is returned to the frame memory 18 as an address signal, to obtain a motion compensation predictive signal 20. The constitution of the encoder side is as mentioned above.
In the decoder side, a transmitted difference signal 13 is decoded in the decorder 25 by means of inverse Huffman coding, inverse quantization, and inverse DCT and motion vector extraction, and the motion vector 22' is given to the motion compensation frame memory 18' to read the motion compensation predictive signal 20' obtained by sliding, from the frame memory 18'. The difference signal 15' decoded in the decorder 25, and the signal 20' read out from the frame memory 18' are added in the adder 16' to generate a picture signal 17, i.e., a local decoded signal. Against the picture signal 17 thus encoded, decoded and reconstruted, a filtering using a postfilter 26 is performed. Alternatively, a filtering using a filter inside loop 23 is performed on the output from the frame memory 18, to reduce a block-shaped noise. Prior art techniques utilized in the above filterings will be described.
As a prior art 1, there is discussed the technique disclosed in "Study of the Method for Improving the Image Quality of Block Encoding Picture by Post Filter Process" by Mitsuya et al. (TECHNICAL REPORT OF IEICE, IE84-46), as shown in FIG. 22. In this technique, the filtering is limited to a block that has less brightness change of an obtained decoded picture, in other words, a block at whose boundary a block distortion is liable to be actualized. That is, a strong smoothing filtering is performed only on a pixel 50 on a block boundary. This filtering is performed by a low-pass filter (hereinafter referred to as "LPF") that takes a simple average of equal weight against nine pixels of a target pixel 40 and its surrounding eight pixels 41 to 48 in FIG. 21. In this figure, numerals 51 and 52 designate a pixel inside a block and a block boundary, respectively.
As a prior art 2, there is discussed the technique described in "Postprocessing Algorithms for Noise Reduction of MPEG Coded Video" by Nakajima et al. (TECHNICAL REPORT OF IEICE, IE94-7, DSP94-7 (1994-04), (hereinafter referred to as "technique of Nakajima")). In the technique of Nakajima, the mixing ratio of a decoded pixel value and a simple average of its surrounding pixel values is changed appropriately depending on the local activity of a picture, quantizing parameter, block activity and the position relation with a block boundary.
Assuming that a local region of the surrounding of the target pixel is a picture region (hereinafter referred to as "local region") of 3.times.3 pixels as shown in FIG. 21, and that a region (hereinafter referred to as "picture block")in which .sigma..sub.b.sup.2 (block activity) is computed is a region of 8.times.8 pixel in which DCT operation as shown in FIG. 20 is performed, the quantizing parameter in decoding is stored for each picture block.
In the local region as shown in FIG. 20, a local average &lt;d (x, y)&gt; is defined by the equation (1) for each of the entire pixels of a decoded picture.
In taking the sum (.SIGMA.) of the local averages, if a pixel is outside the range of a picture region depending on the values of i and j, the value of a target pixel is employed instead of the pixel outside of the picture range. Note that d(x, y) is a decoded pixel value of the coordinate (x, y). ##EQU1##
Then, each pixel dispersion (hereinafter referred to as "local activity") as defined by the equation (2) is obtained in the local region. As the definition of the dispersion, the sum of the square the difference between the local region and the local average of the equation (1) is obtained in each pixel as in the equation (1). ##EQU2##
Picture block dispersion (hereinafter referred to as "block activity") is defined by the equation (3). The block activity is defined for each of the picture blocks B.sub.00 to B.sub.22, as shown in FIG. 20. ##EQU3## wherein x.sub.b, y.sub.b are values of the upper left corner coordinate that belongs to the picture block number b.sub.n.
An m(x, y), d(x, y) and &lt;d(x, y)&gt; are respectively, a corrected pixel value, a decoded pixel value and a simple average pixel value of a local region, in the coordinate (x, y). EQU m(x, y)=(1-.beta.)&lt;d(x, y)&gt;+.beta.d(x, y) (4)
Here, .beta. is a mixing ratio of a decoded value and a value smoothed in the local region. ##EQU4##
In this case, .sigma..sub.bn.sup.2 is a functional value whose variable are quantizing parameter and block activity, and also the experimental value illustrated with the graph in the report. In accordance with the report of Nakajima, .beta. in the above equation (4) is changed so as to increase the proportion of the simple average, in the event that various picture noises are liable to occur, that is, under the following conditions:
a. when quantizing parameter is rough; PA0 b. when block activity is high; PA0 c. when noise occurs in a certain region of a picture; and PA0 d. when a sharp edge exists inside a picture block.
As a prior art 3, a description will be given of the technique of "Gradient Inverse Weighted Smoothing Scheme and the Evaluation of its Performance" by D. C. C. Wang, A. H. Vagnucci and C. C. Li (Comp. Graphics Image Processing, Vol. 15, pp.167-181, 1981) (hereinafter referred to as "technique of Wang"). The technique of Wang is one which takes weighted mean of a target pixel and its surrounding pixels. Its weighting factor is the inverse number of the absolute value of the difference between the target pixel and its surrounding pixels, and defined by the following equations (8) to (11), wherein d(x, y) is a decoded pixel value of the coordinate (x, y); and m(x, y) is a pixel value after taking weighted mean in the coordinate (x, y). ##EQU5##
In this technique, if the difference between a target pixel and its surrounding pixels is small, the weighting factor increases, so that the surrounding pixels are homogenized with a filtered target pixel value. On the contrary, if the difference is great, i.e., if an edge exists, the weighting factor decreases, leading to a filtering that preserves the edge.
As a prior art 4, there will be discussed the technique of a filter utilized in ITU-T advice H. 261 (hereinafter referred to as "H. 261 standard") which was approved by World Telecommunication Standardization Commission. The above filter is employed for an output of a frame memory in which a picture signal of the preceding frame is stored, that is, before obtaining a difference between the present picture signal and an input picture signal (see an in-loop filter 23 in FIG. 24). The output of the above frame memory is filtered by 8.times.8 picture blocks.
The above filter is constituted by operating a primary filter horizontally or vertically, that is, a non-recursive filter having coefficients of 1/4, 1/2, 1/4 against a pixel inside a picture block. In cases where a pixel employed in filter operation is outside the picture block, the above filter functions as a primary filter having coefficients of 0, 1, 0. The filter coefficient at the respective position of the 8.times.8 picture blocks are indicated in FIG. 23, wherein numerals 61, 62, 63 and 64 designate filter coefficients in four corners, up and down ends, right and left ends, and an inner region, respectively. For the up and down ends, and the left and right ends, there are six pixels respectively. In the inner region, there are 36 pixels. The filter coefficient is slided when applying to each pixel.
In these basic filters of the prior art constitution, however, edge information that is inherently possessed by a picture except block noise is to be reduced because uniform filtering is performed on the entire decoded picture. In the case where only a block boundary is filtered using the technique of Mitsuya, when a continuous stroke originally crosses the block boundary, the continuous stroke blurs only on the block boundary. As a result, an observer will have an impression that such a block boundary is unnatural, abnormal or artifact.
The technique of Nakajima utilizes a mixture of a simple average of a decoded pixel value and its surrounding pixels values, so that its filtering blurs edge information within a picture block. Further, as defined in the equation (4), the proportion of a filter having no edge preserving property is enhanced on block boundaries, causing the same problem as in the technique of Mitsuya.
In the technique of Wang having the edge preserving property, the weighting factor of a target pixel is fixed at 1/2, and therefore, plural processing are needed in the identical picture. Further, the replacement of a weighting factor when a pixel difference value .DELTA.D.sub.ij is 0, may underestimate the weighting factor. Since this technique does not take into consideration block noise phenomenon on a block boundary, which occurs in dividing a picture into blocks, a step of a block boundary might be erroneously recognized as an edge to be processed.
The filter of the H. 261 standard also does not have the edge preserving property, causing a blur of a decoded picture.